چه عواملی کاربران را به کامنت‌گذاری در شبکه‌های تجارت اجتماعی ترغیب می‌کند: شواهدی از کاربران اینستاگرام

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشیار، گروه مدیریت، دانشکدگان فارابی، دانشگاه تهران، قم، ایران.

2 استاد، گروه مدیریت، دانشکدگان فارابی، دانشگاه تهران، قم، ایران.

3 استادیار، گروه مدیریت، دانشکده تجارت و بازرگانی، دانشکدگان مدیریت، دانشگاه تهران، تهران. ایران.

4 کارشناس ارشد، گروه مدیریت، دانشکدگان فارابی، دانشگاه تهران، قم، ایران.

10.22059/mmr.2024.386866.1142

چکیده

هدف: در حال حاضر، بسیاری از افراد در شبکه‌های اجتماعی، مانند اینستاگرام، بر اساس انگیزه‌ای فعالیت می‌کنند. افراد در این شبکه برای اظهارنظر از روش‌های مختلفی از جمله استوری، اشتراک متن و تصویر، کامنت‌گذاری و غیره استفاده می‌کنند. هدف از این پژوهش، شناسایی و اولویت‌بندی انگیزه‌های کامنت‌گذاری این افراد است.
روش: پژوهش حاضر از نظر هدف کاربردی و از نظر شیوه گردآوری و تحلیل اطلاعات، توصیفی و از نوع پیمایشی است. جامعۀ آماری این پژوهش، کلیۀ استفاده‌کنندگان از شبکۀ اجتماعی اینستاگرام، در بازه زمانی مهر ۱۴۰۱ تا مرداد ۱۴۰۲ بود. نمونۀ آماری بر اساس فرمول کوکران ۳۸۴ نفر به‌دست آمد که درنهایت ۴۰۰ نفر به آن پاسخ دادند. برای گردآوری داده‌ها، از ابزار پرسش‌نامه استفاده شد. برای رتبه‌بندی انگیزه‌ها، از آزمون فریدمن و نرم‌افزارهای اس‌پی‌اس‌اس و آموس استفاده شد.
یافته‌ها: یافته‌های پژوهش نشان داد که همۀ انگیزه‌های کامنت‌گذاری مطلوب بودند و مهم‌ترین متغیر، متغیر دستیابی به حالت‌های عاطفی مثبت (41/9) است. متغیر تخلیۀ استرس‌ها و فشار روانی (46/8) رتبۀ دوم و به همین ترتیب، متغیر اطلاع‌رسانی به دیگران (95/7) رتبۀ سوم، متغیر اشتراک‌گذاری لذت از یک محصول (79/7) رتبۀ چهارم، متغیر پیشگام‌شدن در تبلیغات دهان‌به‌دهان (51/7) رتبۀ پنجم، متغیر ترویج یک عقیده یا تفکر خاص (77/6) رتبۀ ششم و در نهایت، متغیر تلاش برای مشهور شدن (59/5) رتبۀ آخر را دارد.
نتیجه‌گیری: بسیاری از افراد در دنیای واقعی با استرس‌های روزانه و فشارهای روانی درگیرند. این افراد برای تخلیۀ این احساسات خود، ممکن است به کامنت‌گذاری اقدام کنند. بلاگرها یا سلبریتی‌های مجازی که تمایزهای منحصربه‌فردی دارند، ممکن است هدف این افراد باشند تا این با کامنت‌های خود، فشار روانی وارده را تخلیه کنند. شناسایی این انگیزه و پاسخ‌گویی درست به آن، می‌تواند این حس را در کاربران کنترل کند و کاربردی باشد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

What Factors Motivate Users to Comment on Social Commerce Network: Evidence from Instagram Users

نویسندگان [English]

  • Mohammad Ghaffari 1
  • Hamid Zarea 2
  • Dariush Tahmasebi Aghbelaghi 3
  • Faeze Naderian 4
1 Associate Prof., Department of Management, Farabi Schools, University of Tehran. Qom. Iran.
2 Prof., Department of Management, Farabi Schools, University of Tehran. Qom. Iran.
3 Assistant Prof., Department of Management, Faculty of Commerce and Trade, College of Management, University of Tehran, Tehran, Iran.
4 MS.c., Department of Management, Farabi School, University of Tehran, Qom, Iran.
چکیده [English]

Objective
Communication is currently conceptualized as the act of transmitting or broadcasting content to inform audiences. Communication, as the core of social interaction, is vital for transmitting information between users and helps to understand the thoughts and feelings of others to maintain relationships. Communication also reduces the risk of rejection by providing opportunities for users to understand products and services, exchange information, and participate in co-creation. Currently, many people are active on social networks such as Instagram based on motivation. People on this network use various methods to express opinions, including stories, sharing text and images, commenting, etc. The purpose of this research is to identify and prioritize the motivations of these people for commenting.
Research Methodology
The present study is applied in terms of its purpose and descriptive and survey-type in terms of its method of data collection and analysis. The statistical population of this study was all users of the Instagram social network between October 2022 and August 2023. The statistical sample was 384 people based on the Cochran formula, and 400 people responded to it. Data collection was done using two methods: library and field. In the library method, the motivations for users to comment were extracted by a systematic review of the research literature; to validate the identified motivations, a questionnaire was prepared and filled out by experts; finally, after filling out 20 questionnaires and examining the variables using a single-sample t-test, a number of variables were extracted and a number of new motivations were suggested by experts, which were added to the previous variables. To collect field data, a questionnaire tool consisting of 24 closed-ended questions and 5 demographic questions was used. The validation of the research model was done using confirmatory factor analysis, and the Friedman test was used to rank the motivations using two softwares, SPSS and Amos.
Findings
Finally, the findings of this study were that all the motivations for commenting were desirable, and the most important variable was the variable of achieving positive emotional states (9.41), the second rank was reserved for the variable of relieving stress and psychological pressure (8.46), similarly, the variable of informing others (7.95) ranked third, the variable of sharing the pleasure of a product (7.79) ranked fourth, the variable of being a pioneer in word-of-mouth advertising (7.51) ranked fifth, the variable of promoting a specific idea or thought (6.77) ranked sixth, and the variable of trying to become famous (5.59) ranked last.
Discussion & Conclusion
Instagram is a very practical space for those who want to achieve more fame in a short time, as we see in the case of many bloggers in this space. Less famous users can connect themselves with more famous people by commenting, as we see under the posts of famous people, some comments are pinned that receive more attention than the rest and their owners achieve some kind of fame. Many people in the real world are involved in daily stress and psychological pressure; these people may comment to vent these feelings. Bloggers or virtual celebrities (politicians, movie actors or footballers, etc.) who have unique distinctions may be the target of these people so that they can vent the psychological pressure they are under with their comments. Correctly identifying this motivation and responding to it correctly can properly control this feeling in users and is applicable. The number of users of the Instagram social network is very large, it is also easier to find people who share our beliefs; This is a suitable space for users who have a common intellectual direction, or for people who have religious or political beliefs and want to expand their beliefs or identify like-minded people, this motivation is very applicable. Businesses that have an information aspect for conferences, articles, festivals, discounts, special sales, tourism, participation in classes and training courses can use the motivation of informing others to comment. This motivation is also applicable for audiences who need to obtain information about unknown store businesses. Correct identification of this motivation attracts the audience and increases revenue. All businesses on the Instagram network can use the motivation of being a pioneer in word-of-mouth advertising because this is free and does not cost anything, and on the other hand it also increases revenue and visits.

کلیدواژه‌ها [English]

  • Rating
  • Commenting
  • Social network
  • Commerce network
  • Instagram

مراجع

امامی، علی، بازدار، مهرنوش، صفری، ملیحه و فرحناکی، رامونا (1393). تعیین رابطه حس تعلق و شاخصه‌های اجتماعی آن، نمونه موردی: روستای زیارت در گلستان. معماری و شهرسازی آرمان‌شهر، 10(21)، 21-11.
سلطانی زاده، محمد، ملک پور، مختار و نشاط دوست، حمید طاهر (1387). رابط لذت جسمانی و عاطفه مثبت و منفی در دانشجویان دانشگاه اصفهان. مطالعات روان‌شناختی، 4(14)، 31-46.
سلطانی زاده، محمد، ملک پور، مختار و نشاط دوست، حمید طاهر (1389). رابطه‌ی بین عاطفه‌ی مثبت و منفی با رضایت از زندگی دانشجویان دانشگاه اصفهان. نشریه روان‌شناسی بالینی و شخصیت، 10 (19)، 53-64.
موسوی حق‌شناس، سید میلاد و شاه قاسمی، احسان (1401). تدوین اولویت‌بندی کدهای مسئولیت اجتماعی در فضای مجازی. مطالعات فرهنگ ارتباطات، 23(59)، 7-34.
 
References
Asiamah, N., Kanekar, A., Khan, H. T., Panday, S., & Mensah, S. W. (2022). Neighbourhood walkability as a moderator of the associations between older adults’ information technology use and social activity: A cross-sectional study with sensitivity analyses. Journal of Transport & Health, 26, 10-28. 
Adrian, A. (2008). No one knows you are a dog: Identity and reputation in virtual worlds. Computer Law & Securityreport, 24, 366 -374.
Al-Adwan, A.S. & Kokash, H. (2019). The driving forces of Facebook social commerce. Journal of theoretical and applied electronic commerce research, 14(2), 15-32.
Alamgir Hossain, M. A. & Kim, M. (2020). A comprehensive study on social commerce in social networking sites. Sage Open, 10(2), 1-18.
Algharabat, R. S. & Rana, N. P. (2021). Social commerce in emerging markets and its impact on online community engagement. Information Systems Frontiers, 23, 149-152.
Almoqbel, M. Y., Wohn, D. Y., Hayes, R. A. & Cha, M. (2019). Understanding Facebook news post comment reading and reacting behavior through political extremism and cultural orientation. Computers in Human Behavior, 100, 118-126.
Canavan, B. (2020). Let's get this show on the road! Introducing the tourist celebrity gaze. Annals of Tourism Research, 82,102-98.
Chao, R. F., Fu, Y. & Liang, C. H. (2021). Influence of servicescape stimuli on word-of-mouth intentions: An integrated model to indigenous restaurants. International Journal of Hospitality Management, 96, 10-78.
Chen, L., Baird, A. & Straub, D. (2019). Why do participants continue to contribute? Evaluation of usefulness voting and commenting motivational affordances within an online knowledge community. Decision Support Systems, 118, 21-32.
Chen, R., Yuan, R., Huang, B. & Liu, M. J. (2023). Feeling warm or skeptical? An investigation into the effects of incentivized eWOM programs on customers’ eWOM sharing intentions. Journal of Business Research, 167, 1-7.
Chen, X., Ma, J., Wei, J. & Yang, S. (2020). The role of perceived integration in WeChat usages for seeking information and sharing comments: A social capital perspective. Information & Management, 58(1), 10-80.
Chen, Y., Chen, L. & Smith, R. (2022). Linking passion to performance in the social commerce community: The role of collaborative information exchange. Journal of Business Venturing Insights, 18, 1-20.
Cho, E. & Son, J. (2019). The effect of social connectedness on consumer adoption of social commerce in apparel shopping. Fashion and Textiles, 6(1), 14.
Elgaaied-Gambier, L. & Mandler, T. (2021). Me trying to talk about sustainability: Exploring the psychological and social implications of environmental threats through user-generated content. Ecological Economics, 187, 10-89.
Emami, A., Bazdar, M., Safari, M. & Farahnaki, R. (2023). The determination of relationship between sense of belonging and its social indicators (Case Study: Ziarat Village- Golestan). Armanshahr Architecture & Urban Development, 10(21), 11-21. (in Persian)
Gable, P.A. & Harmon-Jones, E. (2016). Assessing the motivational dimensional model of emotion–cognition interaction: Comment on Domachowska, Heitmann, Deutsch, et al. (2016). Journal of Experimental Social Psychology, 67, 57-59. https://doi.org/10.1016/j.jesp.2015.10.004
Han, J., Park, D., Forbes, H. & Schaefer, D. (2020). A computational approach for using social networking platforms to support creative idea generation. Procedia CIRP, 91, 382-387.
Indrawati, I., Putri Yones, P. C. & Muthaiyah, S. (2023). eWOM via the TikTok application and its influence on the purchase intention of somethinc products. Asia Pacific Management Review, 28(2), 174-184.
Kanani, R. & Glavee-Geo, R. (2021). Breaking the uncertainty barrier in social commerce: The relevance of seller and customer-based signals. Electronic Commerce Research and Applications, 48, 10-59.
Karayiğit, H., Acı, Ç. İ. & Akdağlı, A. (2021). Detecting abusive Instagram comments in Turkish using convolutional Neural network and machine learning methods. Expert Systems with Applications, 174, 11-1.
Kim, J. K., Overton, H., Bhalla, N. & Li, J. Y. (2020). Nike, Colin Kaepernick, and the politicization of sports: Examining perceived organizational motives and public responses. Public Relations Review, 46(2), 101-56.
Kitsios, F., Mitsopoulou, E., Moustaka, E. & Kamariotou, M. (2022). User-Generated Content behavior and digital tourism services: A SEM-neural network model for information trust in social networking sites. International Journal of Information Management Data Insights, 2(1), 100-56.
Konsti-Laakso, S. (2017). Stolen snow shovels and good ideas: The search for and generation of local knowledge in the social media community. Government Information Quarterly, 34(1), 134-139.
Lee, Y. & Kim, K. H. (2020). De-motivating employees’ negative communication behaviors on anonymous social media: The role of public relations. Public Relations Review, 46(4), 10-55.
Li, M. & Tuunanen, T. (2022). Information technology–supported value Co-Creation and Co-Destruction via social interaction and resource integration in service systems. The journal of strategic information systems, 31(2), 10-19.
Li, X., Guo, X. & Shi, Zh. (2023). Bright sides and dark sides: Unveiling the double-edged sword effects of social networks. Social Science & Medicine 329, 11-35.
Lichy, J., Dutot, V. & Kachour, M. (2022). When technology leads social business: Food truck innovation. Technological Forecasting and Social Change, 181, 12-75.
Ma, Y. (2021). To shop or not: Understanding Chinese consumers’ live-stream shopping intentions from the perspectives of uses and gratifications, perceived network size, perceptions of digital celebrities, and shopping orientations. Telematics and Informatics, 59, 10-62.
Maia, C., Lunardi, G., Longaray, A. & Munhoz, P. (2018). Factors and characteristics that influence consumers’ participation in social commerce. Revista de Gestão, 25(2), 194-211.
Meier, S. & Schubert, P. (2023). Social Business Object Ontology (SoBOOnt): A formal description of a novel concept for social features. Procedia Computer Science, 219, 330–338.
Mohamad, A. H., Hassan, G. F. & Abd Elrahman, A. S. (2022). Impacts of e-commerce on planning and designing commercial activities centers: A developed approach. Ain Shams Engineering Journal, 13(4), 10-34.
Mousavi Haghshenas, S.M. & & Shahghasemi, E. (2022). Compilation of priorities for social responsibility codes in cyberspace (Case Study: Citizens of Tehran). Journal of Culture-Communication Studies, 23(59), 7-33. (in Persian)
Poncio, F. P. (2023). An investigation of the gender gap in the information technology and engineering programs through text mining. Decision Analytics Journal, 6, 100158.
Soltanizadeh, M., Malekpour, M. & Neshat Doost, H. (2008). A study of the relationship between physical pleasure, positive and negative affect in Esfahan University students. Journal of Psychological Studies, 4(1), 31-46. (in Persian)
Soltanizadeh, M., Malekpour, M. & Neshatdoost, H. (2013). The relationship between positive and negative affection and student's life satisfaction in University of Isfahan. Clinical Psychology and Personality, 10(2), 53-64. (in Persian)
Stsiampkouskaya, K., Joinson, A., Piwek, L. & Ahlbom, C. P. (2021). Emotional responses to likes and comments regulate posting frequency and content change behaviour on social media: An experimental study and mediation model. Computers in Human Behavior, 124, 10-40.
Tahmasebi Aghbelaghi, D., Jalali, M., Tayim, N. & Kiyani., R. (2024). A network analysis of depression and cognitive impairments in fibromyalgia: A Secondary analysis study. Psychiatr Quarterly, 95 (4), 1-19. https://doi.org/10.1007/s11126-024-10106-6
Tibbetts, M., Epstein-Shuman, A., Leitao, M. & Kushlev, K. (2021). A week during COVID-19: online social interactions are associated with greater connection and more stress. Computers in human behavior reports, 4, 100-133.
Ventre, I., Mollá-Descals, A. & Frasquet, M. (2021). Drivers of social commerce usage: a multi-group analysis comparing Facebook and Instagram. Economic research-Ekonomska istraživanja, 34(1), 570-589.
Wang, G., Zhang, W. & Zeng, R. (2019). WeChat use intensity and social support: The moderating effect of motivators for WeChat use. Computers in Human Behavior, 91, 244-251.
Wang, X., Lin, X. & Spencer, M. K. (2019). Exploring the effects of extrinsic motivation on consumer behaviors in social commerce: Revealing consumers’ perceptions of social commerce benefits. International Journal of Information Management, 45, 163-175.
Wu, D. (2020). Empirical study of knowledge withholding in cyberspace: Integrating protection motivation theory and theory of reasoned behavior. Computers in human behavior, 105, 106-229.
Xu, X. (2021). Closed-form evaluations and open-ended comment options: How do they affect customer online review behavior and reflect satisfaction with hotels? Decision Support Systems, 146, 11-52.
Yang, F. X. & Wong, I. A. (2020). How do cyberspace friendships transition to favorable workplace outcomes? The self-team joint influence. International Journal of Hospitality Management, 85, 102-63.
Zhang, H., Xu, H. & Gursoy, D. (2020). The effect of celebrity endorsement on destination brand love: A comparison of previous visitors and potential tourists. Journal of Destination Marketing & Management, 17, 100-54.
Zhu, M., Liu, L., Su, R. & Contractor, N. (2023). Revisiting the effects of social networks on enterprise collaboration technology use: A fuzzy-set qualitative comparative analysis approach. Decision Support Systems, 174, 11-17.
Zhu, X., Gao, M., Zhang, R. & Zhang, B. (2021). Quantifying emotional differences in urban green spaces extracted from photos on social networking sites: A study of 34 parks in three cities in northern China. Urban Forestry & Urban Greening, 62, 12-33.
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